Virtual assistant configured to automatically customize groups of actions

ABSTRACT

A method includes determining, by an assistant executing at one or more processors, a default group of actions that the assistant is configured to execute in response to receiving a particular audible command. The method includes determining, by the assistant, based on the default group of actions and a user profile associated with a particular user, a custom group of actions that the assistant is configured to execute in response to receiving the particular audible command from the particular user. The method also includes receiving, by the assistant, an indication of the particular audible command, and determining, by the assistant, whether the indication of particular audible command originated from the particular user. The method further includes, responsive to determining that the indication of particular audible command originated from the particular user, executing, by the assistant, each action from the custom group of actions.

BACKGROUND

Some computing platforms may provide a user interface from which a usercan chat, speak, or otherwise communicate with a virtual, intelligent,or computational assistant (e.g., also referred to simply as an“assistant”) to cause the assistant to output information, respond to auser’s needs, or otherwise perform certain operations to help the userperform an action. For instance, a computing device may receive, with amicrophone, voice input (e.g., audio data) that corresponds to a userutterance. An assistant executing, at least in part, at the computingdevice may analyze the voice input and may perform an action based onthe utterance. The assistant may perform a single action based on theutterance. The assistant may perform the same action based on theutterance for all users of the assistant.

SUMMARY

The disclosed subject matter relates to techniques for enabling anassistant to automatically customize groups of actions to individualusers. The assistant determines a customized group of actions to performwhen the assistant receives a particular command from a particular user,and the assistant determines different, customized or default groups ofactions to perform in response to receiving the same particular commandfrom other users. The assistant customizes groups of actions to be morerelevant to individual users, for example, based on an individual’s userprofile, historical behavior, past interactions with the assistant,contextual information, and other information associated with theindividual user. In this way, the assistant is configured toautomatically determine groups of actions that are particularly relevantto an individual user and execute only those particularly relevantactions in response to receiving a command from that individual user.Accordingly, the described techniques may reduce processing power thatwould otherwise be consumed while executing seemingly irrelevant orundesirable actions that may only be helpful or of interest to otherusers. In addition, by automatically creating customized groups ofactions, the assistant may require fewer user inputs to create groups ofactions associated with command, which may further decrease the powerconsumed by the computing device and improve the user experience.Further, in some examples, the assistant may execute a plurality ofactions in parallel, thus increasing the speed at which the actions areexecuted.

Further to the descriptions below, a user may be provided with controlsallowing the user to make an election as to both if and when assistants,computing devices, or computing systems described herein can collect ormake use of personal information, and if and when the user is sentcontent or communications from a server. In addition, certain data maybe treated in one or more ways before it is stored or used, so thatpersonally identifiable information is removed. For example, a user’sidentity may be treated so that no personally identifiable informationcan be determined for the user, or a user’s geographic location may begeneralized where location information is obtained (such as to a city,ZIP code, or state level), so that a particular location of a usercannot be determined. Thus, the user may have control over whatinformation is collected about the user, how that information is used,and what information is provided to the user.

In one example, the disclosure is directed to a method that includesdetermining, by an assistant executing at one or more processors, adefault group of actions that the assistant is configured to execute inresponse to receiving a particular audible command. The method includesdetermining, by the assistant, based on the default group of actions anda user profile associated with a particular user, a custom group ofactions that the assistant is configured to execute in response toreceiving the particular audible command from the particular user. Themethod also includes receiving, by the assistant, an indication of theparticular audible command. The method further includes, determining, bythe assistant, whether the indication of particular audible commandoriginated from the particular user; and responsive to determining thatthe indication of particular audible command originated from theparticular user, executing, by the assistant, each action from thecustom group of actions.

In another example, the disclosure is directed to a computing devicethat includes: an output device, at least one processor, and at leastone memory. The memory includes instructions that when executed, causethe at least one processor to execute an assistant configured todetermine a default group of actions that the assistant is configured toexecute in response to receiving a particular audible command;determine, based on the default group of actions and a user profileassociated with a particular user, a custom group of actions that theassistant is configured to execute in response to receiving theparticular audible command from the particular user; receive, anindication of the particular audible command; determine, whether theindication of particular audible command originated from the particularuser; and responsive to determining that the indication of particularaudible command originated from the particular user, execute each actionfrom the custom group of actions.

In another example, the disclosure is directed to a computer-readablestorage medium comprising instructions that, when executed cause atleast one processor of a digital assistant system to: determine adefault group of actions that the assistant is configured to execute inresponse to receiving a particular audible command; determine, based onthe default group of actions and a user profile associated with aparticular user, a custom group of actions that the assistant isconfigured to execute in response to receiving the particular audiblecommand from the particular user; receive an indication of theparticular audible command; determine whether the indication ofparticular audible command originated from the particular user; andresponsive to determining that the indication of particular audiblecommand originated from the particular user, execute each action fromthe custom group of actions.

In another example, the disclosure is directed to a system includingmeans for determining a default group of actions that the assistant isconfigured to execute in response to receiving a particular audiblecommand; determining, based on the default group of actions and a userprofile associated with a particular user, a custom group of actionsthat the assistant is configured to execute in response to receiving theparticular audible command from the particular user; receiving anindication of the particular audible command; determining whether theindication of particular audible command originated from the particularuser; and responsive to determining that the indication of particularaudible command originated from the particular user, executing eachaction from the custom group of actions.

The details of one or more examples are set forth in the accompanyingdrawings and the description below. Other features, objects, andadvantages of the disclosure will be apparent from the description anddrawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a conceptual diagram illustrating an example system thatexecutes an example virtual assistant, in accordance with one or moreaspects of the present disclosure.

FIG. 2 is a block diagram illustrating an example computing device thatis configured to execute an example virtual assistant, in accordancewith one or more aspects of the present disclosure.

FIG. 3 is a flowchart illustrating example operations performed by oneor more processors executing an example virtual assistant, in accordancewith one or more aspects of the present disclosure.

FIG. 4 is a block diagram illustrating an example digital assistantserver that is configured to execute an example virtual assistant, inaccordance with one or more aspects of the present disclosure.

DETAILED DESCRIPTION

FIG. 1 is a conceptual diagram illustrating an example system thatexecutes an example virtual assistant, in accordance with one or moreaspects of the present disclosure. System 100 of FIG. 1 includes digitalassistant server 160 in communication, via network 130, with computingdevices 110A-110N (collectively, “computing devices 110”) and computingdevices 116A-116N (collectively, “computing devices 116”). Althoughsystem 100 is shown as being distributed amongst digital assistantserver 160, and computing devices 110, 116, in other examples, thefeatures and techniques attributed to system 100 may be performedinternally, by local components of computing devices 110, 116.Similarly, digital assistant server 160 may include certain componentsand perform various techniques that are otherwise attributed in thebelow description to computing devices 110, 116.

Network 130 represents any public or private communications network, forinstance, cellular, Wi-Fi®, and/or other types of networks, fortransmitting data between computing systems, servers, and computingdevices. Digital assistant server 160 may exchange data, via network130, with computing devices 110, 116 to provide a virtual assistantservice that is accessible to computing devices 110,116 when computingdevices 110, 116 are connected to network 130.

Network 130 may include one or more network hubs, network switches,network routers, or any other network equipment, that are operativelyinter-coupled thereby providing for the exchange of information betweenserver system 160 and computing devices 110, 116. Computing devices 110,116, and digital assistant server 160 may transmit and receive dataacross network 130 using any suitable communication techniques.Computing devices 110, 116, and digital assistant server 160 may each beoperatively coupled to network 130 using respective network links. Thelinks coupling computing devices 110, 116, and digital assistant server160 to network 130 may be Ethernet or other types of network connectionsand such connections may be wireless and/or wired connections.

Digital assistant server 160 represents any type of computing devicethat is configured to execute an assistant and communicate on a network.Examples of digital assistant server 160 include cloud computingenvironments, desktop computers, laptop computers, servers, mobilephones, tablet computers, wearable computing devices, countertopcomputing devices, home automation computing devices, televisions,stereos, automobiles, or any other type of mobile or non-mobilecomputing device that is configured to execute a virtual assistantservice.

Computing devices 110 represent individual mobile or non-mobilecomputing devices that are associated with a particular user or userprofile, and are configured to access the virtual assistant serviceprovided via network 130. In some instances, by being associated with aparticular user, one or more of computing devices 110 may be connectedto a particular network that is associated with or frequently accessedby the particular user. For instance, a subset of computing devices 110may be located in a user’s home and may communicate via a home network.In contrast to computing devices 110, computing devices 116 representindividual mobile or non-mobile computing devices that are associatedwith other users or other user profiles (e.g., users other than theparticular users associated with computing devices 110) and configuredto access the virtual assistant service provided via network 130. Inother words, computing devices 110 are associated with a particular userin the example of FIG. 1 , whereas computing devices 116 are associatedwith other users, and not associated with the particular user associatedwith computing devices 110.

Examples of computing devices 110, 116 include a mobile phone, a tabletcomputer, a laptop computer, a desktop computer, a server, a mainframe,a set-top box, a television, a wearable device (e.g., a computerizedwatch, computerized eyewear, computerized gloves, etc.), a homeautomation device or system (e.g., an intelligent thermostat or securitysystem), a home appliance (e.g., a coffee maker, refrigerator, etc.), avoice-interface or countertop home assistant device, a personal digitalassistants (PDA), a gaming system, a media player, an e-book reader, amobile television platform, an automobile navigation or infotainmentsystem, or any other type of mobile, non-mobile, wearable, andnon-wearable computing device. Other examples of computing devices 110,116 may exist beyond those listed above. Computing devices 110, 116 maybe any device, component, or processor, configured to access the virtualassistant service provided via network 130

In the example of FIG. 1 , digital assistant server 160 includesassistant module 122B and user information data store 124B. Computingdevice 110A includes user interface component (UIC) 112, user interface(UI) module 120, assistant module 122, and user information data store124A. Although not shown, computing devices 110B-110N and/or computingdevices 116 may include similar components and/or modules as computingdevice 110A.

Modules 120, 122A, and 122B may perform operations described usingsoftware, hardware, firmware, or a mixture of hardware, software, andfirmware residing in and/or executing at one of computing device 110A ordigital assistant server 160. Computing device 110A and digitalassistant server 160 may execute modules 120, 122A, and 122B withmultiple processors or multiple devices. Computing device 110A anddigital assistant server 160 may execute modules 120, 122A, and 122B asvirtual machines executing on underlying hardware. Modules 120, 122A,and 122B may execute as one or more services of an operating system orcomputing platform. Modules 120, 122A, and 122B may execute as one ormore executable programs at an application layer of an operating systemor computing platform.

UIC 112 of computing devices 110 may function as an input and/or outputdevice for computing device 110A. UIC 112 may be implemented usingvarious technologies. For instance, UIC 112 may function as an inputdevice using presence-sensitive input screens, microphone technologies,infrared sensor technologies, cameras, or other input device technologyfor use in receiving user input. UIC 112 may function as output deviceconfigured to present output to a user using any one or more displaydevices, speaker technologies, haptic feedback technologies, or otheroutput device technology for use in outputting information to a user.

UI module 120 may manage user interactions with UIC 112 and othercomponents of computing device 110A and may interact with digitalassistant server 160 so as to provide assistant services via UIC 112. UImodule 120 may cause UIC 112 to output a user interface as a user ofcomputing device 110A views output and/or provides input at UIC 112. Forexample, as shown in FIG. 1 , UI module 120 may send instructions to UIC112 that cause UIC 112 to display user interface 114A or 114B(collectively, user interfaces 114) at a display screen of UIC 112.

User interfaces 114 include text of conversations between individualusers of computing device 110A and an assistant provided by assistantmodule 122A. In the example of FIG. 1 , user interfaces 114 areprimarily graphical user interfaces, however, user interfaces 114 may insome examples be primarily audible, haptic, or a combination ofgraphical, audible, or haptic type user interfaces. In other words, userinterfaces 114 may include virtual assistant information in variousforms such as audible sounds, voice notifications, vibrations, text,graphics, content cards, images, etc.

UI module 120 and UIC 112 may receive one or more indications of input(e.g., voice input, touch input, non-touch or presence-sensitive input,video input, audio input, etc.) from a user as the user interacts with auser interface of user interfaces 114, at different times and when theuser and computing device 110A are at different locations. UI module 120and UIC 112 may interpret inputs detected at UIC 112 and may relayinformation about the inputs detected at UIC 112 to assistant module122A and/or one or more other associated platforms, operating systems,applications, and/or services executing at computing device 110A, forexample, to cause computing device 110A to perform actions.

UI module 120 may receive information and instructions from one or moreassociated platforms, operating systems, applications, and/or servicesexecuting at computing device 110A and/or one or more remote computingsystems, such as server system 160. In addition, UI module 120 may actas an intermediary between the one or more associated platforms,operating systems, applications, and/or services executing at computingdevice 110A, and various output devices of computing device 110A (e.g.,speakers, LED indicators, audio or haptic output device, etc.) toproduce output (e.g., a graphic, a flash of light, a sound, a hapticresponse, etc.) with computing device 110A. For example, UI module 120may cause UIC 112 to output user interfaces 114 based on data UI module120 receives via network 130 from digital assistant server 160. UImodule 120 may receive, as input from digital assistant server 160and/or assistant module 122A, information (e.g., audio data, text data,image data, etc.) and instructions for presenting as user interfaces114.

Assistant module 122A and assistant module 122B may collaborativelymaintain user information data stores 124A and 124B as part of a virtualassistant service accessed via computing devices 110. Assistant module122B and user information data store 124B represent server-side or cloudimplementations of an example assistant whereas assistant module 122Aand user information data store 124A represent a client-side or localimplementation of the example assistant. In some examples, some or allthe functionality attributed to assistant module 122A may be performedby assistant module 122B, and vice versa.

Referred to collectively as assistant modules 122, assistant module 122Aand assistant module 122B may each include software agents configured toexecute as intelligent personal assistants that can perform actions orservices for an individual, such as a user of computing devices 110.Assistant modules 122 may perform these actions or services based onuser input (e.g., detected at UIC 112), context awareness (e.g., basedon location, etc.), and/or an ability to access other information (e.g.,weather or traffic conditions, news, stock prices, sports scores, userschedules, transportation schedules, retail prices, etc.) from a varietyof information sources (e.g., either stored locally at computing devices110, digital assistant server 160, or obtained via a search or otherinformation retrieval service). Assistant modules 122 may rely on otherapplications (e.g., third-party applications), services, or otherdevices (e.g., televisions, automobiles, watches, home automationsystems, entertainment systems, etc.) to perform actions or services foran individual.

After receiving explicit user consent, assistant modules 122 mayautomatically maintain information associated with a user, or pointersto locations of information associated with a user (e.g., stored byinformation sources located at computing devices 110, server system 160,or by any other server or device located elsewhere on network 130).Assistant modules 122 may maintain the information, or pointers toinformation, associated with the user as user information data stores124A and 124B (collectively “user information data stores 124”). Datastores 124 may enable the assistant executed by assistant modules 122 toquickly access user information required by the assistant to complete areal-world action, a virtual action, or otherwise respond to immediateand/or future needs of the user of computing devices 110. Assistantmodules 122 may permit a user to revoke access to and/or delete copiesof information associated with the user.

Data stores 124 may include one or more user profiles that are eachassociated with a respective user of computing devices 110, 116. Forexample, a user profile may include information obtained, withpermission from the user, during a conversation or interaction betweenthe user and the assistant, calendar information, contact information,user interests, user preferences, and any other information associatedwith a user that may be used by assistant modules 122. Examples ofsources of information for a user profile may include, but are notlimited to, intelligence built in an e-mail system, user interactionswith assistant modules 122, user interactions and application usage ondevices associated with the user (e.g., computing devices 110), or othersources of information.

In accordance with techniques of this disclosure, assistant modules 122may provide an assistant that executes at, or is accessible from,computing devices 110. In general, assistant modules 122 may beconfigured to execute one or more routines that each include a pluralityof actions and may customize the routine for different user profiles. Inother words, as used herein, the term “routine” generally refers to agroup of actions performed by assistant modules 122 together (e.g., inparallel or serially) at approximately the same time. As used throughoutthis disclosure, at approximately the same time means within a thresholdor predetermined amount of time, such as one second, thirty seconds, oneminute, five minutes, etc. (e.g., as opposed to an exact instant intime).

Assistant modules 122 may be configured to execute a particular routinein response to receiving a particular command from a particular user(e.g., “Computer, I’m off to work”) and may execute a different routinein response to receive a different command from the particular user(e.g., “Computer, I’m headed home”). In other words, different commandsmay correspond to different routines. In some instances, a particularroutine may be associated with multiple commands. For instance, amorning routine may be associated with the command “Hey computer, I’mawake” or the command “Computer, let’s get the day started.” In someexamples, each routine includes a plurality of actions executable byassistant modules 122. Hence, in some examples, one or more assistantmodules 122 are configured to execute a plurality of actions in responseto receiving a particular command (e.g., an audible command).

In some examples, assistant modules 122 determine a default group ofactions that assistant modules 122 are configured to execute in responseto receiving the particular command. In other words, assistant modules122 determine a default group of actions that are included in a routineassociated with the particular command. Assistant modules 122 maydetermine the default group of actions by retrieving a pre-programmedgroup of actions from a memory device. The default group of actions maybe programmed at a factory or may be received as part of a softwareupdate from an application developer. In some instances, the defaultgroup of actions are initially associated with all users of computingdevices 110 and 116.

Assistant modules 122 may determine the default group of actions usingmachine learning. For example, assistant modules 122 determine, in someinstances, a default group of actions by analyzing what actions users ofcomputing devices 110, 116 cause assistant modules 122 to performtogether and in different circumstances. The actions that appear mostfrequently across different scenarios or contexts may form a defaultgroup of actions that assistant module 122 determines is generallyapplicable to all users of computing devices 110, 116.

Assistant modules 122 may generate the default group of actionsassociated with a command by utilizing machine learning to analyzeindividual user and/or device information stored in user informationdata stores 124. Assistant modules 122 may only analyze informationassociated with computing devices 110, 116 and/or users of computingdevices 110, 116 if the users affirmatively consent to use or collectionof such information. Assistant modules 122 may further provideopportunities for individual users to withdraw consent and in whichcase, assistant modules 122 may cease collecting or otherwise retainingthe information associated with the individual user or computing devicesassociated with the individual user. User profiles within data stores124 may include user interaction data indicating how often users ofcomputing devices 110 and/or 116 utilize certain applications and/orapplication features, request certain types of information (e.g.,weather, traffic), or otherwise interact with computing devices 110, 116and/or assistant modules 122.

Assistant modules 122 may identify actions that users of computingdevices 110, 116 frequently perform, actions that users of computingdevices 110, 116 frequently utilize computing devices 110, 116 toperform, or both. For instance, assistant module 122B may determine,based at least in part on past user interaction data (also referred toas action usage data) stored in data stores 124, that users of computingdevices 110, 116 often request news and weather information fromcomputing devices 110, 116 in the morning. Thus, in some examples,assistant modules 122 determines the default group of actions for amorning routine include outputting the news and weather information.Thus, assistant modules 122 may determine that the default group ofactions corresponding to a particular command (e.g., a commandassociated with a morning routine, such as “Good morning computer” or“Computer, let’s get the day started”) include outputting the news andweather information.

In some examples, assistant modules 122 determines a custom group ofactions that assistant modules 122 are configured to execute as part ofa routine. Assistant modules 122 may determine the custom group ofactions based on the default group of actions and a user profileassociated with a particular user of computing devices 110. As describedabove, information associated with a user profile may be stored in oneor more of data stores 124. In some examples, assistant modules 122 maydetermine (e.g., based on user information for the user profileassociated with a particular user) whether one or more actions from thedefault group of actions associated with a particular command arerelevant to the user associated with the particular user profile. Forinstance, data stores 124 may include a user profile for a particularuser that includes user interaction data indicating how much the usercauses computing devices 110 to perform a particular action. The userinteraction data may indicate that the particular user rarely (e.g.,once a month) requests news information in the morning, such thatassistant modules 122 may determine that news information is notrelevant to that particular user. Thus, in some scenarios, assistantmodules 122 generates a custom group of activities for the particularuser that does not include the news information.

Assistant modules 122 may determine the custom group of actionsassociated with a particular command includes an action that is notincluded in the default group of actions. For example, assistant modules122 may determine, based on user interaction data within a user profilethat is stored in data stores 124, that the particular user requeststraffic information every day at approximately the same time (e.g.,within a threshold amount of time of a certain time). Assistant modules122 may add an action to a custom group of actions based on the userinformation associated with the particular user. For example, assistantmodules 122 may update the custom group of actions to include startingthe user’s vehicle and outputting traffic information.

In some examples, assistant modules 122 are configured to execute agroup of actions in response to receiving a particular command. Forexample, assistant modules 122 may receive an indication of user input(e.g., a gesture, audible command, etc.), determine whether the userinput corresponds to a particular command, and execute a group ofactions (e.g., a group of actions associated with a particular routine)in response to determining that the user input corresponds to theparticular command. For example, UIC 112 may detect a gesture at apresence-sensitive display and may send an indication of the gesture toassistant modules 122. Assistant modules 122 may determine whether thegesture corresponds to a particular command. As another example, UIC 112may detect audio data (e.g. a spoken audio command) and may send anindication of the audio data to assistant modules 122. Assistant modules122 may determine whether the audio data includes a particular audiocommand (e.g., by performing speech recognition techniques on the audiodata). In some examples, assistant modules 122 are configured to executea group of actions in response to determining that the audio dataincludes the particular command.

In some scenarios, assistant modules 122 receives an indication of acommand and determines whether the command originated from a particularuser. For instance, assistant modules 122 may receive an indication ofan audible command “Computer, tell me about my day.” Responsive toreceiving the indication of the command, assistant modules 122 determinewhether the command originated from a particular user. Assistant modules122 may determine whether the command originated from the particularuser based on biometrics (e.g., voice, face, or handwritingrecognition). For example, user information data store 124A may includea voice fingerprint for the particular user and may compare theindication of the audible command to the voice fingerprint to determinewhether an audible command was spoken by the particular user. Forinstance, assistant module 122A may determine that the audible commandwas spoken by the particular user in response to determining that thespoken command corresponds to the voice fingerprint for the particularuser. In some examples, computing device 110A may capture one or moreimages prior to, during, and/or after receiving a command and assistantmodule 122A may determine whether a command originated from theparticular user based on the one or more images. For instance, assistantmodule 122A may perform facial recognition on at least one capturedimage and may determine that the command originated from the particularuser in response to determining that at least one captured imageincludes an image of the particular user.

In some examples, assistant modules 122 determine that the command didnot originate from the particular user. For instance, computing device110 may be located at the user’s home, may receive the audible command“Hey computer, tell me about my day,” and may determine (e.g., based onvoice recognition) that the particular user did not speak the command.Responsive to determining that the command did not originate from theparticular user, assistant modules 122 may execute one or more actionsfrom the default group of actions. For instance, as illustrated by userinterface 114A, when the default group of actions includes outputtingnews and weather information, assistant modules 122 may cause one ormore of computing devices 110 to output the news and weatherinformation.

Responsive to determining that the command originated from theparticular user, assistant modules 122 may execute one or more actionsfrom the custom group of actions associated with the particular user.For example, when the custom group of actions includes outputtingweather and traffic information, and starting the user’s vehicle,assistant modules 122 may cause one or more computing devices 110 tooutput the weather and traffic information and start the user’s vehicle.For instance, as illustrated by user interface 114B, assistant modules122 may cause computing device 110A (e.g., a counter top home assistant,which may not have a display device) to audibly output weatherinformation and computing device 110B (e.g., within a vehicle) to startthe vehicle and output for display (e.g., via a display device withinthe vehicle) to display traffic information (e.g., a traffic map).

In some instances, assistant modules 122 execute one or more actions(e.g., actions in a default group of actions or a custom group ofactions) at approximately the same time. For instance, assistant modules122 may output news and weather information at approximately the sametime (e.g., sequentially).

While assistant modules 122 are described as being configured to executea group of actions (e.g., a default group of actions or a custom groupof actions) in response to receiving an audible command, assistantmodules 122 may be configured to execute a group of actions that areincluded in a routine in response to a detecting a triggering event,such as an occurrence of a scheduled event (e.g., a calendar event, analarm, etc.), receipt of a predetermined notification, receipt of acommand (e.g., gesture input, or audible input), etc. For example, whenthe triggering event includes an alarm set to occur at a scheduled time,assistant modules 122 may execute a group of actions associated with aparticular routine in response to the alarm occurring. As anotherexample, when the triggering event includes receiving a notificationthat a door (e.g., a garage door) has opened (e.g., upon a userreturning home after work) or closed (e.g., upon a user leaving forwork), assistant modules 122 may execute a group of actions associatedwith opening or closing the door. Assistant modules 122 may determine adefault group of actions and a custom group of actions that assistantmodules 122 are configured to execute in response to detecting thetriggering event, and may execute the default or custom group of actionsin response to detecting the triggering event.

In contrast to some computing devices that execute one action percommand, assistant modules 122 may execute a group of actions inresponse to receiving a single command. In this way, assistant modules122 may reduce the number of commands required to execute a group ofactions, which may reduce processing performed by one or more computingdevices. Further, by associating a group of actions with a singlecommand, assistant modules 122 may reduce data traffic on network 130between computing device 110A and server 160 (e.g., to perform voicerecognition on spoken commands), data traffic on a communication bus(e.g., communication channel 250 of FIG. 2 ), calls to memory, batteryusage, etc. Reducing the number of commands required to execute a groupof actions may improve the user experience by making the assistant seemnatural, less awkward, and more desirable to the user. By automaticallycustomizing a group of actions for an individual user, assistant modules122 may execute only those actions that are determined to beparticularly relevant to the user, which may reduce processing performedby one or more computing devices. Further, by automatically customizingthe group of actions for an individual, the assistant may require feweruser inputs to create groups of actions, which may decrease the powerconsumed by one or more computing devices.

Among the several benefits provided by the aforementioned approach are:(1) the processing complexity and time for a device to act may bereduced by executing a group of actions in response to a trigger ratherthan executing actions one at a time; (2) meaningful information andinformation associated with the user may be stored locally reducing theneed for complex and memory-consuming transmission security protocols onthe user’s device for the private data; (3) because the exampleassistant executes groups of actions in response to a trigger, fewerspecific inquiries or commands may be received from the user, therebyreducing demands on a user device for query rewriting and othercomputationally complex data retrieval; and (4) network usage may bereduced as a quantity of specific inquires and/or commands is reduced.

FIG. 2 is a block diagram illustrating an example computing device thatis configured to execute an example virtual assistant, in accordancewith one or more aspects of the present disclosure. Computing device 210of FIG. 2 is described below as an example of computing devices 110, 116of FIG. 1 . FIG. 2 illustrates only one particular example of computingdevice 210, and many other examples of computing device 210 may be usedin other instances and may include a subset of the components includedin example computing device 210 or may include additional components notshown in FIG. 2 .

As shown in the example of FIG. 2 , computing device 210 includes userinterface component (UIC) 212, one or more processors 240, one or morecommunication units 242, one or more input components 244, one or moreoutput components 246, and one or more storage components 248. UIC 212includes output component 202 and input component 204. Storagecomponents 248 of computing device 210 include UI module 220, assistantmodule 222, user information data store 224, and one or more applicationmodules 226.

Communication channels 250 may interconnect each of the components 212,240, 242, 244, 246, and 248 for inter-component communications(physically, communicatively, and/or operatively). In some examples,communication channels 250 may include a system bus, a networkconnection, an inter-process communication data structure, or any othermethod for communicating data.

One or more communication units 242 of computing device 210 maycommunicate with external devices via one or more wired and/or wirelessnetworks by transmitting and/or receiving network signals on the one ormore networks. Examples of communication units 242 include a networkinterface card (e.g. such as an Ethernet card), an optical transceiver,a radio frequency transceiver, a global positioning satellite (GPS)receiver, or any other type of device that can send and/or receiveinformation. Other examples of communication units 242 may include shortwave radios, cellular data radios, wireless network radios, as well asuniversal serial bus (USB) controllers.

One or more input components 244 of computing device 210 may receiveinput. Examples of input are tactile, audio, and video input. Inputcomponents 244 of computing device 210, in one example, includes apresence-sensitive input device (e.g., a touch sensitive screen, a PSD),mouse, keyboard, voice responsive system, video camera, microphone orany other type of device for detecting input from a human or machine. Insome examples, input components 244 may include one or more sensorcomponents, such as one or more location sensors (e.g., GPS components),one or more temperature sensors, one or more movement sensors (e.g.,accelerometers, gyros), one or more pressure sensors, and one or moreother sensors (e.g., an audio sensor such as a microphone, an opticalimage sensor, infrared proximity sensor, and the like). Other sensorsmay include a heart rate sensor, magnetometer, glucose sensor,hygrometer sensor, olfactory sensor, compass sensor, step countersensor, to name a few other non-limiting examples.

One or more output components 246 of computing device 110 may generateoutput. Examples of output are tactile, audio, and video output. Outputcomponents 246 of computing device 210, in one example, includes a PSD,sound card, video graphics adapter card, speaker, cathode ray tube (CRT)monitor, liquid crystal display (LCD), or any other type of device forgenerating output to a human or machine.

UIC 212 of computing device 210 may be similar to UIC 112 of computingdevice 110 and includes output component 202 and input component 204.Output component 202 may be a display component, such as a screen atwhich information is displayed by UIC 212 and input component 204 may bea presence-sensitive input component that detects an object at and/ornear output component 202. Output component 202 and input component 204may be a speaker and microphone pair or any other combination of one ormore input and output components, such as input components 244 andoutput components 246. In the example of FIG. 2 , UIC 212 may present auser interface (such as user interfaces 114 of FIG. 1 ).

While illustrated as an internal component of computing device 210, UIC212 may also represent an external component that shares a data pathwith computing device 210 for transmitting and/or receiving input andoutput. For instance, in one example, UIC 212 represents a built-incomponent of computing device 210 located within and physicallyconnected to the external packaging of computing device 210 (e.g., ascreen on a mobile phone). In another example, UIC 212 represents anexternal component of computing device 210 located outside andphysically separated from the packaging or housing of computing device210 (e.g., a monitor, a projector, etc. that shares a wired and/orwireless data path with computing device 210).

One or more storage components 248 within computing device 210 may storeinformation for processing during operation of computing device 210(e.g., computing device 210 may store data accessed by modules 220, 222,and 226, and data store 224 during execution at computing device 210).In some examples, storage component 248 is a temporary memory, meaningthat a primary purpose of storage component 248 is not long-termstorage. Storage components 248 on computing device 210 may beconfigured for short-term storage of information as volatile memory andtherefore not retain stored contents if powered off. Examples ofvolatile memories include random access memories (RAM), dynamic randomaccess memories (DRAM), static random access memories (SRAM), and otherforms of volatile memories known in the art.

Storage components 248, in some examples, also include one or morecomputer-readable storage media. Storage components 248 in some examplesinclude one or more non-transitory computer-readable storage mediums.Storage components 248 may be configured to store larger amounts ofinformation than typically stored by volatile memory. Storage components248 may further be configured for long-term storage of information asnon-volatile memory space and retain information after power on/offcycles. Examples of non-volatile memories include magnetic hard discs,optical discs, floppy discs, flash memories, or forms of electricallyprogrammable memories (EPROM) or electrically erasable and programmable(EEPROM) memories. Storage components 248 may store program instructionsand/or information (e.g., data) associated with modules 220, 222, and226, and data store 224. Storage components 248 may include a memoryconfigured to store data or other information associated with modules220, 222, and 226, and data store 224.

One or more processors 240 may implement functionality and/or executeinstructions associated with computing device 210. Examples ofprocessors 240 include application processors, display controllers,auxiliary processors, one or more sensor hubs, and any other hardwareconfigure to function as a processor, a processing unit, or a processingdevice. Modules 220, 222, and 226 may be operable by processors 240 toperform various actions, operations, or functions of computing device210. For example, processors 240 of computing device 210 may retrieveand execute instructions stored by storage components 248 that causeprocessors 240 to perform the operations modules 220, 222, and 226. Theinstructions, when executed by processors 240, may cause computingdevice 210 to store information within storage components 248, forexample, at data stores 224.

UI module 220 may include all functionality UI module 120 of FIG. 1 andmay perform similar operations as UI module 120 for executing anassistant as part of computing device 210. UI module 220 may manage userinteractions with UIC 212 and other components of computing device 210.UI module 220 may cause UIC 212 to output a user interface as a user ofcomputing device 210 views output and/or provides input at UIC 212.

User information data store 224 is an example of user information datastore 124A of FIG. 1 . User information data store 224 may include oneor more user profiles associated with respective users of computingdevice 210 and/or users of other computing devices (e.g., computingdevices 116 of FIG. 1 ). In some examples, a user profile may includeuser information obtained with permission from the user. For example,each user profile may include information obtained during a conversationor interaction between the user and the assistant. Each user profile mayinclude information indicative the user’s interests and/or userpreferences. A user profile may include user interaction data, which mayindicate when and/or how much the user causes an assistant to performcertain actions. In some examples, a user profile may includebiographical information associated with the user, such as a geographiclocation (e.g., a city, state, or country where the user resides), ageof the user, occupation, etc.

Application modules 226 represent various individual applications andservices that may be executed by computing device 210 and that may beaccessed by an assistant to provide user with information and/or performa task or action. Examples of application modules 226 include a fitnessapplication, a calendar application, a search application, a map,traffic, or navigation application, a travel application (e.g.,planning, reservation, ticketing, etc.), a social media application, agame application, an e-mail application, a chat or messagingapplication, an Internet browser application, or any other applicationsthat may execute at computing device 210. An assistant executing atcomputing device 210, such as assistant module 222, may causeapplications 226 to execute instructions for performing actionsassociated with the assistant. In other words, the assistant may rely onapplication modules 226 to perform one or more actions on behalf of theassistant.

Assistant module 222 may include all functionality of assistant modules122 of FIG. 1 and may perform similar operations as assistant modules122 for executing an assistant as part of computing device 210 andmaintaining and accessing user information at user information datastore 224. In some examples, assistant module 222 may execute locally(e.g., at processors 240) to provide assistant functions. In someexamples, assistant module 222 may act as an interface to a remoteassistant service accessible to computing device 210. For example,assistant module 222 may be an interface or application programminginterface (API) to assistant module 122B of digital assistant server 160of FIG. 1 .

Assistant module 222 may be configured to execute a group of actions inresponse to a triggering event, such as an occurrence of a scheduledevent (e.g., a calendar event, an alarm, etc.), receipt of apredetermined notification, or receipt of a command (e.g., gesture, oraudible command). For example, assistant module 222 may be configured toexecute a group of actions that are part of a routine associated with aparticular (e.g., audible) command.

As one example, a morning routine may be associated with an audiblecommand such as “Hey computer, let’s get the day started” and the groupof actions performed with the morning routine may include outputtingnews information and traffic information and brewing a cup of coffee. Anafternoon routine may be associated with the audible command “Computer,I’m headed home” and the group of actions performed with the afternoonroutine may include outputting traffic information and calendarinformation (e.g., for events later that evening). An evening routinemay be associated with the audible command “Ok computer, what is goingon tomorrow?” and the group of actions performed with the eveningroutine may include outputting calendar information (e.g., for the nextday) and adjusting an alarm (e.g., based on an early morning meeting).

Each group of actions executed as part of a routine may be associatedwith one or more audible commands. The audible commands may or may notrequire a response from assistant module 222. For example, assistantmodule 222 may be configured to execute a group of actions in responseto receiving an audible command that requests a response, such as “Heycomputer, tell me about my day.” Similarly, assistant module 222 may beconfigured to execute a group of actions in response to receiving anaudible command that does not include a request for a response, such as“Hey computer, I’m going to work.”

Assistant module 222 may be configured to execute a default group ofactions associated with a particular command. In some examples, adefault group of actions is associated with all users who utilize anassistant and in other examples, a default group of actions associatedwith a particular command may only be associated with a subset of users(e.g., users of computing devices 210, 110, and/or 116). For instance,assistant module 222 may determine a first group of default actionsassociated with a particular command for a first subset of users and asecond group of default actions associated with the same command for asecond (e.g., different than the first) subset of users.

In some examples, assistant module 222 groups users into varioussubsets. For example, assistant module 222 may determine a subset ofusers as including a type of users that are similar to one another. Forexample, assistant module 222 may determine that a group of users ofcomputing devices 210, 110, and/or 116 are similar based on one or moreuser profiles stored in a user information data store (e.g., data store224). For instance, assistant module 222 may determine that a group ofusers are similar in response to determining that user profilesassociated with respective users indicate the users are from a similargeographic area (e.g., city, state, country), have similar interests,speak the same language, are within the same age group, have similarjobs, cause computing devices 210, 116 to perform similar actions, etc.For instance, assistant module 222 may determine that a first type ofuser includes users living in England and a second type of user includesusers living in France.

Assistant module 222 may determine that different types of users areassociated with different types of routines. In some examples, assistantmodule 222 may determine (e.g., based on information stored in userprofiles) that a first type of user (e.g., a person who works outsidethe home) is associated with a morning routine (e.g., a group of actionsperformed before going to work), an afternoon routine (e.g., a group ofactions performed before returning home), and an evening routine (e.g.,a group of actions performed in preparation for the next day). Forexample, assistant module 222 may determine that the first type of userfrequently causes computing device 210 or other assistant enablecomputing devices to perform various actions in the morning, afternoon,and evening. Similarly, assistant module 222 may determine that a secondtype of user (e.g., a stay-at-home parent) is associated with a morningroutine, a lunch routine, a shopping routine, a play-time routine, etc.For example, assistant module 222 may determine that the second type ofuser frequently causes computing device 210 or other assistant enablecomputing devices to perform various actions in the morning,mid-morning, mid-day, mid-afternoon, and evening. Assistant module 222may determine each routine is associated with different commands andincludes actions associated with the respective commands.

In some examples, assistant module 222 determines a default group ofactions associated with a particular command. The default group ofactions may be associated with all users of computing devices 210, 110,116 or may be associated with a particular type of similar users. Thedefault group of actions associated with a particular command mayinclude one or more actions to output information (e.g., visually oraudibly for human consumption), one or more actions to perform a task,or one or more other types of actions or a combination therein. Examplesof tasks include brewing a cup of coffee, turning lights on or off,opening or closing a garage door, adjusting a thermostat, recording ashow, playing music, placing an order, creating or annotating anelectronic list, or any other conceivable action that an assistant mayperform other than outputting information via a user interface (e.g.,other than outputting information for human consumption).

In some examples, assistant module 222 determines the default group ofactions by querying storage devices 248 to retrieve a pre-programmedgroup of actions. The pre-programmed group of actions may be programmedat a factory or may be received as part of a software update from asoftware developer.

Assistant module 222 may determine the default group of actionsassociated with a particular command by utilizing a model generated bymachine learning techniques. Example machine learning techniques thatmay be employed to generate a model can include various learning styles,such as supervised learning, unsupervised learning, and semi-supervisedlearning. Example types of models generated via such techniques includeBayesian models, Clustering models, decision-tree models, regularizationmodels, regression models, instance-based models, artificial neuralnetwork models, deep learning models, dimensionality reduction modelsand the like.

In some examples, assistant module 222 applies the model to one or moreinputs and outputs a default group of actions. After receiving explicitconsent from users, assistant module 222 may apply the model to userinformation (e.g., from one or more user profiles stored in data store224 and/or data stores 124) to identify actions that a user of computingdevice 210 is likely to cause computing device 210 to perform.

In some instances, the default group of actions include actions thatappear most frequently across different scenarios or contexts. Forexample, assistant module 222 may apply the model to determine actionsfrequently performed by computing device 210, actions performed by othercomputing devices associated with an individual user of computing device210, and actions performed by computing devices (e.g., computing devices116 of FIG. 1 ) that are associated with other users. For instance, themodel may be trained on user information indicating that 85% of users ofcomputing devices (e.g., computing devices 210, 110, and 116) requestweather information in the morning, that 80% of the users requesttraffic information in the morning, and that 30% of users brew a cup ofcoffee in the morning. Assistant module 222 may compare how often anaction is performed to a threshold usage amount (e.g., 50% of users). Insome examples, assistant module 222 determines that the default group ofactions include actions where the usage of that action satisfies (e.g.,is greater than or equal to) the threshold usage amount. Thus, in someinstances, assistant module 222 may determine that a routine (e.g., amorning routine) associated with a particular command (e.g., “Heycomputer, tell me about my day”) includes an action to output trafficinformation and an action to output weather information, and may notinclude an action to brew a cup of coffee.

In some examples, the default group of actions includes actions that areassociated with one another. Two or more actions may be associated withone another when users perform and/or cause computing devices to performthe two or more actions at approximately the same time. Assistant module222 may determine that two or more actions are associated with oneanother and are part of a default group of actions in response todetermining that a threshold amount of individual users (e.g., athreshold amount of all users or a threshold amount of a particularsubset of similar users) cause computing devices associated with each ofthe respective users to perform the two or more actions at approximatelythe same time (e.g., within a threshold window of time of requestingweather information). In other words, assistant module 222 may determinethat two or more actions are associated with one another when athreshold amount of users cause one or more respective computing devicesto perform each action. For example, the model may be trained on userinformation indicating that 65% of users request both weather andtraffic information in the morning. Thus, in such examples, assistantmodule 222 may determine that a routine (e.g., a morning routine)associated with a particular command (e.g., “Hey computer, tell me aboutmy day”) includes an action to output traffic information and an actionto output weather information.

In some examples, assistant module 222 determines whether to customize agroup of actions that are associated with a particular user and aparticular command. Assistant module 222 may determine whether tocustomize the group of actions based at least in part on a user profilethat is stored in user information data store 224 and is associated withthe particular user. In some examples, the user profile includes one ormore indications of explicit and/or implicit feedback from a user, suchthat assistant module 222 may determine whether to customize the groupof actions associated with a particular user and particular commandbased on explicit and/or implicit feedback from a user. For example, theuser profile may include an indication of explicit feedback, such as anexplicit command to include, and/or refrain from including, one or moreactions in a custom group of actions. For instance, computing device 210may receive an explicit command (e.g., “hey computer, don’t tell me thenews when I ask about my day”) such that assistant module 222 maydetermine that assistant module 222 should customize the group ofactions associated with that command. Thus, in some examples, assistantmodule 222 may update the user profile associated with the particularuser to indicate the user is not interested in news information.Assistant module 222 may update the user profile to indicate that thegroup of actions associated with that particular command should notinclude news information, or to indicate that none of the groups ofactions associated with the particular user (e.g., regardless of thecommand) should include news information.

In some examples, assistant module 222 may output a notification (e.g.,an audible message) that includes a request for explicit feedback abouta particular action. For example, assistant module 222 may receive anindication that a new action is available for one or more computingdevices associated with the particular user and may request explicitfeedback from the user. A developer of a particular application module226 may add a feature to the particular application module 226 enablingcomputing device 210 to perform a new action in response to receiving aparticular command. A computing device manufacturer (e.g., anintelligent thermostat manufacturer) may add a new feature to thecomputing device. Assistant module 222 may receive (e.g., from theapplication developer or device manufacturer) an indication of the newaction, and may determine to customize the group of actions associatedwith the particular command and particular user in response to receivingthe indication of the new action.

Responsive to determining that a new action (e.g., remotely adjusting athermostat) exists for a vehicle associated with the user, assistantmodule 222 may output a notification indicative of the new action andrequesting further instructions from the user. For instance, assistantmodule 222 may cause an output device (e.g., a speaker) to output amessage “Did you know I can adjust the temperature in your car? Wouldyou like me to turn on the AC as part of your afternoon routine?”Responsive to receiving a command to add the new action to a group ofactions (e.g., a group of actions associated particular routine),assistant module 222 may customize the group of actions associated witha particular command to include the new action. For instance, assistantmodule 222 may determine that the custom group of actions associated thecommand “Hey computer, I’m heading home in 5 minutes” includes executingone or more actions associated with the vehicle, such as adjusting thetemperature inside the vehicle cabin.

In some instances, assistant module 222 may determine whether tocustomize a group of actions associated with a particular command andparticular user based on implicit feedback, such as repeated userinteractions. For instance, a user information data store (e.g., datastore 224) may include a user profile associated with the particularuser that indicates how much the particular user commands assistantmodule 222 (or an assistant module on other computing devices associatedwith the particular user) to perform various actions. Responsive toreceiving an indication of a particular command at least a threshold athreshold number of times (or at least a threshold number of timeswithin a certain period of time) from a particular user, assistantmodule 222 may determine to customize a group of actions associated withthe particular command. In other words, assistant module 222 maydetermine to customize a group of actions associated with a particularcommand and a particular user after receiving the particular command atleast a threshold number of times from the particular user.

Assistant module 222 may customize a group of actions associated with aparticular command and a particular user in response to determining thata computing device which was not previously associated with theparticular user is now associated with the particular user. In someexamples, the particular user may purchase a vehicle with a computingdevice that includes an assistant module, such that assistant module 222may update the user profile corresponding to the particular user toindicate that a group of computing devices associated with theparticular user includes the new vehicle. In these examples, assistantmodule 222 may customize a group of actions associated with a particularcommand in response to determining that the user is associated with anassistant enabled vehicle. Thus, in some instances, assistant module 222may customize the group of actions associated with the command“Computer, I’m off to work” by adding actions associated with thevehicle (e.g., remotely starting the vehicle, adjusting the cabintemperature, etc.) to that group of actions.

In some examples, assistant module 222 customizes a group of actions inresponse to receiving a notification. For example, assistant module 222may receive a notification from another computing device (e.g., anassistant enabled computing device associated with the particular user)or from an application or service executing at or accessible fromcomputing device 210 and may customize the group of actions associatedwith a particular command in response to receiving the notification. Forinstance, a countertop home assistant device may receive a command(e.g., “Computer, tell my spouse to pick up milk on the way home”) froma spouse of the user of computing device 210. Assistant module 222 ofcomputing device 210 may customize a group of actions associated with anafternoon routine in response to receiving the command. As anotherexample, computing device 210 may receive a notification (e.g., a textmessage) and may store an indication of the notification in the userprofile. For instance, computing device 210 may receive a text messagethat includes a message “Will you please pick up milk on the way home?”and may add a reminder to pick up milk to the user profile. Thus,assistant module 222 may customize the group of actions associated witha particular command for an afternoon routine (e.g., “Hey computer,let’s get ready to go home”) to include outputting a notification ormessage that includes a reminder to pick up milk.

In some examples, assistant module 222 determines a custom group ofactions associated with a particular command and a particular user. Forexample, assistant module 222 may create a new custom group of actionsand/or update an existing custom group of actions to include one or moreactions that are relevant to the particular user (e.g., and to aparticular routine).

Assistant module 222 determines whether a particular action is relevantto a particular user by determining and assigning a relevancy score tothe action and comparing the relevancy scores to a relevancy threshold.The relevancy score for a particular action may indicate a probabilitythat a user will cause assistant module 222 to perform that action.Assistant module 222 may determine that a particular action (e.g.,outputting weather information) is relevant to the user when therelevancy score corresponding to the action satisfies (e.g., is greaterthan or equal to) the relevancy threshold.

Assistant module 222 may generate a custom group of actions by modifyingor updating an existing, default group of actions. For instance,assistant module 222 may assign a relevancy score to each action from adefault group of actions that are associated with the particular commandto determine whether any of the actions from the default group ofactions are relevant to a particular user (e.g., by satisfying arelevancy threshold) and therefore should be included in a custom groupof actions. In some cases, assistant module 222 may assign relevancyscores to one or more actions that are not already included in a defaultgroup of actions. Assistant module 222 may generate custom group ofactions by combining any actions, either from a default group or notfrom a default group, that have relevancy scores that satisfy arelevancy threshold, and are associated with a particular command orroutine. In this way, the actions included in a custom group of actionsmay include one or more actions from a default group of actionsassociated with a command and/or one or more actions that are notnecessarily part of the default group of actions.

Assistant module 222 may assign a relevancy score based on explicit userfeedback. For instance, assistant module 222 may receive an explicitcommand (e.g., “hey computer, don’t tell me the news when I ask about myday”) and may assign a relevancy score (e.g., 0 out of 100) to an actionassociated with (e.g., an action identified by) that command. In someexamples, assistant module 222 assigns a relevancy score to respectiveactions based on the user interaction data within the user profilestored in data store 224. For example, assistant module 222 may assign ahigher relevancy score to a particular action the more the user causescomputing device 210 to perform that action. For instance, assistantmodule 222 may assign a high relevancy score (e.g., 90 out of 100) to aparticular action if the user causes computing device 210 to execute theaction several times a week, a medium relevancy score (e.g., 50 out of100) if the user causes computing device 210 to execute the action oncea week, and a low relevancy score (e.g., 20 out of 100) if the usercauses computing device 210 to execute the action less than once a week.Assistant module 222 may determine whether the relevancy scorecorresponding to a particular action satisfies (e.g., is greater than orequal to) a relevancy threshold and may include the particular actionwithin a custom group of actions in response to determining that therelevancy score corresponding to a particular action satisfies arelevancy threshold.

As one example, assistant module 222 may determine that data store 224includes information indicating the particular user frequently (e.g.,every week day) causes computing device 210 to adjust a home thermostatat approximately the same time that the user leaves for work and mayassign a relatively high (e.g., 90 out of 100) relevancy score based onthe usage information. Thus, in this example, assistant module 222determines that the custom group of actions associated with that commandand the particular user includes adjusting the thermostat (e.g., eventhough the default group of actions associated with a command for amorning routine might not include adjusting the thermostat). In someexamples, assistant module 222 determines that the custom group ofactions does not include a particular action (e.g., an action from thedefault group of actions) in response to determining that thecorresponding relevancy score does not satisfy a relevancy threshold.For example, data store 224 may include information indicating theparticular user rarely (e.g., once a month) causes computing device 210to brew a cup of coffee. Assistant module 222 may assign a relativelylow (e.g., 10 out of 100) relevancy score based on the usageinformation. Thus, while the default group of actions associated with acommand for a morning routine may include brewing coffee, the customgroup of actions associated with that command and the particular usermay not include brewing coffee.

In some examples, assistant module 222 determines the custom group ofactions based on a type of computing device with which the user isinteracting. For example, assistant module 222 may determine therelevancy score for a particular action based on the type of computingdevice the user interacts with. For instance, when the particular userinteracts with computing device 210, assistant module 222 may assign onerelevancy score to a particular action when computing device 210 is acertain type of computing device and another relevancy score to the sameaction when computing device 210 is a different type of computingdevice. In some examples, when a user interacts with a particular typeof computing device 210 (e.g., a mobile phone, vehicle head unit, etc.),assistant module 222 may assign a higher relevancy score to actionswhich the particular type of computing device is configured to perform.

For example, when the particular user interacts with computing device210 and computing device 210 includes a vehicle head unit, assistantmodule 222 may assign a relatively high (e.g., higher than a threshold)relevancy score to an action for outputting traffic information and arelatively low (e.g., lower than a threshold) relevancy score to brewingcoffee. Thus, assistant module 222 may determine that the custom groupof actions associated with the command “Computer, let’s get the daystarted” includes outputting traffic information (e.g., visually) butdoes not include turning on a coffeemaker when computing device 210 is avehicle.

As another example, when computing device 210 includes a countertop homeassistant device, assistant module 222 may assign a relatively high(e.g., lower than a threshold) relevancy score to brewing coffee. Thus,in some instances, assistant module 222 may determine that the customgroup of actions associated with the particular user and the command“Computer, let’s get the day started” includes turning on a coffee makerwhen computing device 210 includes a countertop home assistant device.In this way, assistant module 222 may determine that the custom group ofactions includes one group of actions when computing device 210 is acertain type of computing device and another group of actions whencomputing device 210 is a different type of computing device.

Assistant module 222 may receive an indication of a particular command.For example, UIC 212 may detect a keyboard input, gesture input, oraudible input indicative of a command and may send an indication of thecommand to assistant module 222. In some examples, assistant module 222may receive an indication of the particular command from anothercomputing device (e.g., an intelligent lock or garage door opener) via acommunication unit 242. For instance, responsive to receiving a commandto open a garage door (e.g., upon a user returning home from work) anintelligent garage door opener may send a notification indicative of thecommand to open the door to computing device 210, such that assistantmodule 222 may receive the notification indicative of the command toopen the door. As another example, assistant module 222 may receive anindication of an audible command “Computer, tell me about my day.”

Responsive to receiving an indication of a particular command, assistantmodule 222 may determine whether the command originated from aparticular user. Assistant module 222 may determine whether the commandoriginated from the particular user based on biometrics (e.g., voice,face, or handwriting recognition). For example, user information datastore 224 may include a voice fingerprint for the particular user andmay compare the indication of the audible command to the voicefingerprint to determine whether an audible command was spoken by theparticular user. For instance, assistant module 222 may determine thatthe audible command was spoken by the particular user in response todetermining that the spoken command corresponds to the voice fingerprintfor the particular user. Assistant module 222 may capture one or moreimages prior to, during, and/or after receiving a command and maydetermine whether a command originated from the particular user based onthe one or more images. For instance, assistant module 222 may performfacial recognition on at least one captured image and may determine thatthe command originated from the particular user in response todetermining that at least one captured image includes an image of theparticular user.

Responsive to determining that the command did not originate from theparticular user, assistant module 222 may execute one or more actionsfrom the default group of actions associated with the particularcommand. In some examples, assistant module 222 may execute each actionfrom the default group of actions. For example, responsive to receivinga command “Hey computer, tell me about tonight” and determining thecommand did not originate from the particular user (e.g., assistantmodule 222 may determine the voice producing the command is for anunknown user), assistant module 222 may output weather information andinformation about nearby activities occurring that evening.

Responsive to determining that the command originated from theparticular user, assistant module 222 may determine whether a customgroup of actions associated with the command exists for the particularuser. For instance, assistant module 222 may query a user informationdata store (e.g., one or more of data stores 224 and/or 124) todetermine whether the data store includes a custom group of actions forthe particular user. In some examples, assistant module 222 determines(e.g., based on the query results) that a custom group of actionsassociated with the particular command and the particular user does notexist. Responsive to determining that a custom group of actionsassociated with the particular command and the particular user does notexist, assistant module 222 may execute at least one action from adefault group of actions associated with the particular command. Forexample, assistant module 222 may execute one or more actions associatedwith the particular command and a particular type of user. For instance,when the particular user is a first type of user (e.g., a user living ina particular geographic area), assistant module 222 may query userinformation data store 224 to determine a group of actions associatedwith the particular command and that type of user.

Assistant module 222 may execute one or more actions from the customgroup of actions in response to determining that the command originatedfrom the particular user. In some scenarios, assistant module 222 mayexecute one or more actions from the custom group of actions in responseto determining that the command originated from the particular user andthat a custom group of actions associated with the command exists forthe particular user. Assistant module 222 may execute each action fromthe custom group of actions. Assistant module 222 may execute aplurality (e.g., all or a subset) of actions from the custom group ofactions by causing one or more computing devices associated with theuser to execute each action in the plurality of actions. For instance,when the custom group of actions includes brewing a cup of coffee,adjusting a temperature in a vehicle, and outputting trafficinformation, assistant module 222 may output a message to a coffeemaker(e.g., one of computing devices 110 of FIG. 1 ) instructing thecoffeemaker to brew a cup of coffee, a message to a vehicle instructingthe vehicle to adjust the temperature in the vehicle cabin, and outputaudio data (e.g., audibly outputting information) indicative of theexpected traffic conditions. Thus, a first computing device (e.g., acoffeemaker) may execute a first action of the custom group of actions,a second computing device (e.g., a vehicle head unit) may execute asecond action of the custom group of actions, and a third computingdevice (e.g., computing device 210) may execute a third action of thecustom group of actions. In some examples, assistant module 222 mayoutput a message to another computing device (e.g., the coffeemaker)directly (e.g., via Bluetooth®, or via Wi-Fi® when both computing device210 and the other computing device are on the same home network). Insome examples, assistant module 222 may output a message to message toanother computing device indirectly via another computing device, suchas a server. For example, assistant module 222 may output a message toserver 160 of FIG. 1 , such that assistant module 122B may send amessage to the coffeemaker to brew the coffee. While described asutilizing three computing devices to execute the actions in the customgroup of actions, assistant module 222 may cause any number (e.g., one,two, five, etc.) of computing devices to execute actions from the customgroup of actions.

In some examples, the custom group of actions includes at least oneaction to be executed each time a particular command is received. Forexample, assistant module 222 may cause one or more computing devicesassociated with the user to output weather information and trafficinformation each time that a particular command is received (e.g., eachtime the command “Computer, tell me about my day” is received from theparticular user). In some instances, the custom group of actionsincludes one or more actions to be executed a predetermined number oftimes (e.g., once, twice, etc.). For instance, responsive to receiving anotification that includes a message from a user’s spouse to “pick upmilk on the way home”, assistant module 222 of computing device 210 maycause computing device 210 to output a message that includes a reminderto pick up milk a single time (e.g., the next time assistant module 222receives a command associated with an afternoon routine). In somescenarios, assistant module 222 may customize the group of actionsassociated with that particular command to include outputting anotification when that particular command is received from theparticular user within a particular period of time (e.g., within thenext 24 hours).

FIG. 3 is a flowchart illustrating example operations performed by oneor more processors executing an example virtual assistant, in accordancewith one or more aspects of the present disclosure. FIG. 3 is describedbelow in the context of computing device 110 of FIG. 1 . For example,assistant module 122B, while executing at one or more processors ofcomputing device 110A, may perform operations 300-316, in accordancewith one or more aspects of the present disclosure.

In operation, computing device 110A receives consent from a user to makeuse of and store the personal information (300). For instance, inresponse to identifying potential personal information, assistant module122B may cause UI module 120 to request permission from the user tostore and make use of personal information obtained during interactionswith assistant module 122B and the user. It should be understood thatcomputing device 110A may not require a user to consent prior to eachtime that assistant module 122B wants to make use of or store personalinformation. For example, if computing devices 110A receives consentonce a year, once a day, or even just one time (e.g., after initialproduct purchase, set up, etc.) computing device 110A may treat thatprior consent as consent to make use and store personal information inthe future.

Assistant module 122B determines a default group of actions that theassistant is configured to execute in response to receiving a particularaudible command (302). In other words, assistant module 122B maydetermine a default group of actions that is associated with aparticular command and the assistant module 122B may be configured toexecute the default group of actions in response to receiving theparticular audible command. In some examples, assistant module 122Bdetermines a default group of actions that are associated with all usersof assistant module 122B. Assistant module 122B may determine a defaultgroup of actions that are associated with a particular type of user.Assistant module 122B may determine the default group of actions byquerying a pre-programmed group of actions. In some examples, assistantmodule 122B determines the default group of actions using machinelearning. For example, assistant module 122B may apply a model to userinformation stored in data store 124B and may output a group of actionsassociated with a particular command.

Assistant module 122B determines whether to customize a group of actionsassociated with a particular command for a particular user (304). Forinstance, assistant module 122B may be configured to execute a customgroup of actions in response to receiving the particular audible commandfrom a particular user. Assistant module 122B may determine whether tocustomize a group of actions based at least in part on a user profileassociated with the particular user. In some examples, the user profileincludes one or more indications of explicit and/or implicit feedbackfrom a user, such that assistant module 122B may determine whether tocustomize the group of actions associated with a particular user andparticular command based on explicit and/or implicit feedback from auser. For instance, assistant module 122B may receive a commandproviding explicit feedback (e.g., “Computer, add starting my vehicle tomy morning routine”) such that assistant module 122B may determine thatassistant module 122B should customize the group of actions associatedwith a command for a morning routine. In some examples, the user profileincludes user interaction data and may determine to customize the groupof actions based on the user interaction data. For instance, a user mayfrequently command assistant module 122B to brew a cup of coffee in themorning, such that assistant module 122 may determine to customize agroup of actions associated with a particular command (e.g., that isassociated with a morning routine) in response to determining that theparticular user has requested assistant module 122B to perform theaction at least a threshold amount. In some examples, assistant module122B determines to customize the group of actions associated with aparticular command in response to receiving a notification. As anotherexample, assistant module 122B may customize the group of actionsassociated with a command in response to determining that a newcomputing device which was not previously associated with the particularuser is now associated with the particular user.

In some instances, responsive to determining to customize a group ofactions associated with a particular command (“YES” branch of 304),assistant module 122B determines a custom group of actions associatedwith a particular command and a particular user (305). For instance,assistant module 122B may determine a custom group of actions associatedwith a particular command and a particular user by generating a customgroup of actions. Assistant module 122B may determine a custom group ofactions by updating an existing custom group of actions (e.g., by addingand/or removing actions) associated with a particular command and aparticular user. The custom group of actions may include one or moreactions from the default group of actions associated with the particularcommand, one or more actions that are not included in the default groupof actions associated with the particular command. In some instances,the custom group of actions does not include one or more actions fromthe default group of actions associated with the particular command.Assistant module 122B may assign a relevancy score to one or morerespective actions (e.g., based on the user profile for a particularuser) and may compare the respective relevancy scores to relevancythreshold. For instance, assistant module 122B may assign a relativelyhigh relevancy score (e.g., 100 out of 100) to a particular action(e.g., locking a door) in response to receiving explicit feedback from auser (e.g.., “hey computer, lock the door when I go to work”). In someexamples, assistant module 122B determines that the custom group ofactions includes a particular action in response to determining therelevancy score satisfies the relevancy threshold.

Assistant module 122B receives an indication of the particular command(306). For example, UIC 112 may detect a user input indicating a commandand may send an indication of the command to assistant module 122B. Forinstance, UIC 112 may include a microphone that detects audiblecommands, and may send an indication of an audible command to assistantmodule 122B in response to detecting an audible command.

Assistant module 122B determines whether the indication of particularaudible command originated from the particular user (308). For example,assistant module 122B may perform voice recognition on the data receivedfrom UIC 112 to determine whether the particular user spoke theparticular command. In some examples, assistant module 122B may receivean indication of one or more images (e.g., captured by an image sensorof computing device 110A at approximately the same time an audiblecommand was received). Assistant module 122B may perform facialrecognition on at least one captured image and may determine that thecommand originated from the particular user in response to determiningthat at least one captured image includes an image of the particularuser.

Responsive to determining that the indication of particular audiblecommand originated from the particular user (“NO” branch of 308),assistant module 122B executes each action from the default group ofactions (310). For instance, assistant module 122B may cause one or moreof computing devices 110 to execute various actions from the defaultgroup of actions.

Responsive to determining that the indication of particular audiblecommand originated from the particular user (“YES” branch of 308),assistant modules 122 determines whether a custom group of actions forthe particular user and particular audible command exists (312). In someexamples, assistant module 122B queries a user information data store(e.g., one or more of data stores 224 and/or 124) to determine whetherthe data store includes a custom group of actions for the particularuser. For example, assistant module 122B may determine that a customgroup of actions associated with the particular user and particularcommand exists in response to receiving information indicating of one ormore groups of custom actions associated with the particular user andparticular command and may determine that a custom group of actions doesnot exist in response to the query returning an empty set.

Assistant module 122B executes at least one action from a default groupof actions associated with a type of the particular user and theparticular command (316) in response to determining that a custom groupof actions associated with the particular user and particular commanddoes not exist (“NO” branch of 312). For example, assistant module 122Bmay determine a type of user for the particular user and query userinformation data stores 124 for actions associated with that type ofuser. Responsive to receiving an indication of one or more actionsassociated with that type of user, assistant module 122B executes atleast one of the one or more actions. For instance, assistant module122B may send a command to one or more computing devices associated withthe particular user to execute one or more actions from the defaultgroup of actions associated with that type of user.

Responsive to determining that a custom group of actions associated withthe particular user and particular command does exist (“YES” branch of312), assistant module 122B executes one or more actions from the customgroup of actions associated with the particular user and particularcommand (314). In some examples, assistant module 122B executes eachaction from the custom group of actions. Assistant module 122B may causecomputing devices 110 to perform one or more of the actions in thecustom group of actions. For example, when computing device 110Aincludes a countertop home assistant device and the custom group ofactions includes outputting weather information, assistant module 122Bmay cause computing device 110A to output (e.g., audibly) the weatherinformation. In some examples, assistant module 122B may cause anothercomputing device associated with the user to execute one or more actionsfrom the default group of actions. For example, when the custom group ofactions includes outputting traffic information and computing device110B includes a vehicle head unit, assistant module 122B may causecomputing device 110B to output (e.g., for display) the trafficinformation.

FIG. 4 is a block diagram illustrating an example computing system thatis configured to execute an example virtual assistant, in accordancewith one or more aspects of the present disclosure. Digital assistantserver 460 of FIG. 4 is described below as an example of digitalassistant server 160 of FIG. 1 . FIG. 4 illustrates only one particularexample of digital assistant server 460, and many other examples ofdigital assistant server 460 may be used in other instances and mayinclude a subset of the components included in example digital assistantserver 460 or may include additional components not shown in FIG. 4 .

As shown in the example of FIG. 4 , digital assistant server 460includes one or more processors 440, one or more communication units442, and one or more storage devices 448. Storage devices 448 includeassistant module 422, user information data store 424, and search module482.

Processors 440 are analogous to processors 240 of computing system 210of FIG. 2 . Communication units 442 are analogous to communication units242 of computing system 210 of FIG. 2 . Storage devices 448 areanalogous to storage devices 248 of computing system 210 of FIG. 2 .Communication channels 450 are analogous to communication channels 250of computing system 210 of FIG. 2 and may therefore interconnect each ofthe components 440, 442, and 448 for inter-component communications. Insome examples, communication channels 450 may include a system bus, anetwork connection, an inter-process communication data structure, orany other method for communicating data.

User information data store 424 is analogous to user information datastore 224 of FIG. 2 and is configured to store information associated bythe user that assistant module 422 has learned about the user of acomputing device during conversations between the user and an assistantprovided by assistant module 422. Assistant module 422 may rely on theinformation stored at data store 424, to determine events and selectactions related to the events for inclusion in notifications sent byassistant module 422.

Assistant module 422 may include some or all functionality of assistantmodules 122 of FIG. 1 and assistant module 222 of computing device 210of FIG. 2 . Assistant module 422 may perform similar operations asassistant modules 122 and 222 for providing an assistant service that isaccessible via a network, such as network 130. That is, assistant module422 may act as an interface to a remote assistant service accessible toa computing device that is communicating over a network with digitalassistant server 460. For example, assistant module 422 may be aninterface or API to assistant module 122B of digital assistant server160 of FIG. 1 .

In operation, assistant module 422 may determine a default group ofactions associated with a particular (e.g., audible) command. Thedefault group of actions may be associated with all users of computingdevices 110, 116 or a subset of users (e.g., a type of users that aresimilar to one another). For example, assistant module 422 may determinethe default group of actions by retrieving a pre-programmed group ofactions from a memory device. Assistant module 422 may determine thedefault group of actions by applying a model to user information storedin data store 424. The default group of actions may include actions thatusers of computing devices 110, 116 frequently perform, utilizecomputing devices 110, 116 to perform, or both. The default group ofactions may include frequently performed actions (e.g., the mostfrequently performed actions or the most frequently executed at acertain time of day, such as morning, afternoon, evening, etc.). In someexamples, the default group of actions includes actions associated withone another (e.g., when a threshold amount of users who perform oneaction also perform a second action at approximately the same time).

Assistant module 422 may determine whether to customize a group ofactions associated with a particular command and a particular user.Assistant module 422 may determine whether to customize a group ofactions based at least in part on a user profile associated with theparticular user. In some examples, the user profile includes one or moreindications of explicit and/or implicit feedback from a user, such thatassistant module 422 may determine whether to customize the group ofactions associated with a particular user and particular command basedon explicit and/or implicit feedback from a user. Assistant module 422may determine to customize the group of actions associated with aparticular command in response to receiving a notification. In someinstances, assistant module 422 may determine to customize the group ofactions associated with a particular command in response to determiningthat a new computing device which was not previously associated with theparticular user is now associated with the particular user.

Assistant module 422 may determine a custom group of actions based onthe default group of actions and a user profile associated with theparticular user. For example, data store 424 may include a user profileassociated with the particular user, such as usage information,interests, etc. Assistant module 422 may include a particular action inthe custom group of actions in response to determining that theparticular action is relevant to the particular user. For example,assistant module 422 may assign a relevancy score to one or more actionsbased on the information in the user profile (e.g., action usageinformation, user interests, etc.) and determines that a particularaction is relevant to that particular user when the relevancy scoresatisfies (e.g., is greater than or equal to) a relevancy threshold. Insome examples, assistant module 422 determines whether to include anaction in a custom group of actions based on a type of computing devicewith which the user is interacting.

Assistant module 422 may receive an indication of a command. Forexample, computing device 110A of FIG. 1 may receive an input indicativeof a command (e.g., a keyboard input, a gesture, an audible command) andmay send an indication of the command to computing device 460. Assistantmodule 422 may receive the indication of the command and may determinewhether the command originated from a particular user in response toreceiving an indication of a particular command. For instance, assistantmodule 422 may determine whether the command originated from theparticular user based on biometrics (e.g., voice, face, or handwritingrecognition). For example, user information data store 424 may include avoice fingerprint for the particular user and may compare the indicationof the audible command to the voice fingerprint to determine whether anaudible command was spoken by the particular user. For instance,assistant module 422 may determine that the audible command was spokenby the particular user in response to determining that the spokencommand corresponds to the voice fingerprint for the particular user.

Responsive to determining that the command did not originate from theparticular user, assistant module 422 may execute one or more actionsfrom the default group of actions. For instance, when the default groupof actions includes outputting news and weather information, assistantmodule 422 may cause one or more of computing devices 110 to output thenews information and weather information.

Responsive to determining that the command originated from theparticular user, assistant module 422 may execute one or more actionsfrom the custom group of actions associated with the particular user.For example, when the custom group of actions includes outputtingweather and traffic information, and starting the user’s vehicle,assistant module 422 may cause one or more computing devices 110 tooutput the weather and traffic information and start the user’s vehicle.For instance, assistant module 422 may cause a first computing device(e.g., a counter top home assistant, which may not have a displaydevice) to audibly output weather information and a second, differentcomputing device (e.g., within a vehicle) to start the vehicle andoutput for display (e.g., via a display device within the vehicle) todisplay traffic information (e.g., a traffic map).

The following numbered examples may illustrate one or more aspects ofthe disclosure:

Example 1. A method comprising: determining, by an assistant executingat one or more processors, a default group of actions that the assistantis configured to execute in response to receiving a particular audiblecommand; determining, by the assistant, based on the default group ofactions and a user profile associated with a particular user, a customgroup of actions that the assistant is configured to execute in responseto receiving the particular audible command from the particular user;receiving, by the assistant, an indication of the particular audiblecommand; determining, by the assistant, whether the indication ofparticular audible command originated from the particular user; andresponsive to determining that the indication of particular audiblecommand originated from the particular user, executing, by theassistant, each action from the custom group of actions.

Example 2. The method of example 1, wherein the indication of theparticular audible command is a first indication of the particularaudible command, the method further comprising: receiving, by theassistant, a second indication of the particular audible command;determining, by the assistant, whether the second indication ofparticular audible command originated from the particular user; andresponsive to determining that the second indication of particularaudible command did not originate from the particular user, executing,by the assistant, each action from the default group of actions.

Example 3. The method of any one of examples 1-2, wherein executing eachaction from the custom group of actions comprises causing one or morecomputing devices associated with the user to execute each action fromthe custom group of actions.

Example 4. The method of any one of examples 1-3, further comprising:determining, by the assistant, whether a custom group of actionsassociated with the particular user and particular command exists inresponse to determining that the indication of the particular audiblecommand originated from the particular user, wherein executing eachaction from the custom group of actions is further responsive todetermining that the custom group of actions associated with theparticular user and particular command exists.

Example 5. The method of example 4, wherein the indication of theparticular audible command is a first indication of the particularaudible command that is received at a first time, the method furthercomprising: receiving, by the assistant, a second indication of theparticular audible command at a second time that is earlier than thefirst time; determining, by the assistant, whether the second indicationof particular audible command originated from the particular user; andresponsive to determining that the second indication of the particularaudible command originated from the particular user, determining, by theassistant, whether a custom group of actions associated with theparticular user and particular command does not exist; responsive todetermining that the custom group of actions associated with theparticular user and particular command exists, executing, by theassistant, each action from a default group of actions that areassociated with the particular command and a type of user correspondingto the particular user.

Example 6. The method of any one of examples 1-5, further comprising:determining, by the assistant, whether the assistant has received anindication of the particular audible command at least a threshold numberof times, wherein determining the custom group of actions is responsiveto determining that the assistant has received an indication of theparticular audible command at least the threshold number of times.

Example 7. The method of any one of examples 1-6, wherein determiningthe custom group of actions is responsive to determining that a newcomputing device is associated with the particular user.

Example 8. The method of examples 7, further comprising: determining, bythe assistant, a new action associated with the new computing device,outputting, by the assistant, an indication of the new action; andreceiving, by the assistant, an indication of a command to add the newaction to the custom group of actions, wherein determining the customgroup of actions is further responsive to receiving the indication ofthe command to add the new action to the custom group of actions.

Example 9. The method of any one of examples 1-8, wherein determiningthe custom group of actions further comprises determining the customgroup of actions based on a type of computing device the particular useris interacting with.

Example 10. The method of any one of examples 1-9, wherein the customgroup of actions includes an action to be executed each time theparticular audible command is received and an action to be executed apredetermined number of times.

Example 11. The method of any one of examples 1-10, wherein executingeach action from the group of actions comprises: executing, by a firstcomputing device, at least a first action from the custom group ofactions; and executing, by a second computing device, at least a secondaction from the custom group of actions.

Example 12. A computing system comprising: an output device; at leastone processor; and at least one memory comprising instructions that whenexecuted, cause the at least one processor to execute an assistantconfigured to: determine a default group of actions that the assistantis configured to execute in response to receiving a particular audiblecommand; determine, based on the default group of actions and a userprofile associated with a particular user, a custom group of actionsthat the assistant is configured to execute in response to receiving theparticular audible command from the particular user; receive, anindication of the particular audible command; determine, whether theindication of particular audible command originated from the particularuser; and responsive to determining that the indication of particularaudible command originated from the particular user, execute each actionfrom the custom group of actions.

Example 13. The computing system of example 12, wherein the assistant isfurther configured to: receive, a second indication of the particularaudible command; determine, whether the second indication of particularaudible command originated from the particular user; and responsive todetermining that the second indication of particular audible command didnot originate from the particular user, execute each action from thedefault group of actions.

Example 14. The computing system of any one of examples 12-13, whereinthe assistant is further configured to: determine whether a custom groupof actions associated with the particular user and particular commandexists in response to determining that the indication of the particularaudible command originated from the particular user; and execute eachaction from the custom group of actions in further response todetermining that the custom group of actions associated with theparticular user and particular command exists.

Example 15. The computing system of example 14, wherein the indicationof the particular audible command is a first indication of theparticular audible command that is received at a first time, wherein theassistant is further configured to: receive a second indication of theparticular audible command at a second time that is earlier than thefirst time; determine whether the second indication of particularaudible command originated from the particular user; responsive todetermining that the second indication of the particular audible commandoriginated from the particular user, determine whether a custom group ofactions associated with the particular user and particular command doesnot exist; and responsive to determining that the custom group ofactions associated with the particular user and particular commandexists, execute each action from a default group of actions that areassociated with the particular command and a type of user correspondingto the particular user.

Example 16. The computing system of any one of examples 11-14, whereinthe assistant is further configured to: determine whether the assistanthas received an indication of the particular audible command at least athreshold number of times, determine the custom group of actions inresponse to determining that the assistant has received an indication ofthe particular audible command at least the threshold number of times.

Example 16. The computing system of any one of examples 11-15, whereinthe assistant is further configured to determine the custom group ofactions in response to determining that a new computing device isassociated with the particular user.

Example 17. The computing system of example 16, wherein the assistant isfurther configured to: determine a new action associated with the newcomputing device, output an indication of the new action; and receive anindication of a command to add the new action to the custom group ofactions, wherein the assistant is configured to determine the customgroup of actions in further response to receiving the indication of thecommand to add the new action to the custom group of actions.

Example 18. The computing system of any one of examples 11-17, whereinthe assistant is configured to determine the custom group of actionsfurther based on a type of computing device the particular user isinteracting with.

Example 19. The computing system of any one of examples 11-18, whereinthe custom group of actions includes an action to be executed each timethe particular audible command is received and an action to be executeda predetermined number of times.

Example 20. A computer-readable storage medium comprising instructionsthat, when executed cause at least one processor of a digital assistantsystem to: determine a default group of actions that the assistant isconfigured to execute in response to receiving a particular audiblecommand; determine, based on the default group of actions and a userprofile associated with a particular user, a custom group of actionsthat the assistant is configured to execute in response to receiving theparticular audible command from the particular user; receive anindication of the particular audible command; determine whether theindication of particular audible command originated from the particularuser; and responsive to determining that the indication of particularaudible command originated from the particular user, execute each actionfrom the custom group of actions.

Example 21. A computing device comprising at least one processor and atleast one memory comprising instructions that when executed, cause theat least one processor to perform the method of any one of examples1-11.

Example 22. A computer-readable storage medium comprising instructionsthat, when executed cause at least one processor of a computing deviceto perform the method of any one of examples 1-11.

Example 23. A system comprising means for performing the method of anyone of examples 1-11.

In one or more examples, the functions described may be implemented inhardware, software, firmware, or any combination thereof. If implementedin software, the functions may be stored on or transmitted over, as oneor more instructions or code, a computer-readable medium and executed bya hardware-based processing unit. Computer-readable medium may includecomputer-readable storage media or mediums, which corresponds to atangible medium such as data storage media, or communication mediaincluding any medium that facilitates transfer of a computer programfrom one place to another, e.g., according to a communication protocol.In this manner, computer-readable medium generally may correspond to (1)tangible computer-readable storage media, which is non-transitory or (2)a communication medium such as a signal or carrier wave. Data storagemedia may be any available media that can be accessed by one or morecomputers or one or more processors to retrieve instructions, codeand/or data structures for implementation of the techniques described inthis disclosure. A computer program product may include acomputer-readable medium.

By way of example, and not limitation, such computer-readable storagemedia can comprise RAM, ROM, EEPROM, CD-ROM or other optical diskstorage, magnetic disk storage, or other magnetic storage devices, flashmemory, or any other storage medium that can be used to store desiredprogram code in the form of instructions or data structures and that canbe accessed by a computer. Also, any connection is properly termed acomputer-readable medium. For example, if instructions are transmittedfrom a website, server, or other remote source using a coaxial cable,fiber optic cable, twisted pair, digital subscriber line (DSL), orwireless technologies such as infrared, radio, and microwave, then thecoaxial cable, fiber optic cable, twisted pair, DSL, or wirelesstechnologies such as infrared, radio, and microwave are included in thedefinition of medium. It should be understood, however, thatcomputer-readable storage mediums and media and data storage media donot include connections, carrier waves, signals, or other transientmedia, but are instead directed to non-transient, tangible storagemedia. Disk and disc, as used herein, includes compact disc (CD), laserdisc, optical disc, digital versatile disc (DVD), floppy disk andBlu-ray disc, where disks usually reproduce data magnetically, whilediscs reproduce data optically with lasers. Combinations of the aboveshould also be included within the scope of computer-readable medium.

Instructions may be executed by one or more processors, such as one ormore digital signal processors (DSPs), general purpose microprocessors,application specific integrated circuits (ASICs), field programmablelogic arrays (FPGAs), or other equivalent integrated or discrete logiccircuitry. Accordingly, the term “processor,” as used herein may referto any of the foregoing structure or any other structure suitable forimplementation of the techniques described herein. In addition, in someaspects, the functionality described herein may be provided withindedicated hardware and/or software modules. Also, the techniques couldbe fully implemented in one or more circuits or logic elements.

The techniques of this disclosure may be implemented in a wide varietyof devices or apparatuses, including a wireless handset, an integratedcircuit (IC) or a set of ICs (e.g., a chip set). Various components,modules, or units are described in this disclosure to emphasizefunctional aspects of devices configured to perform the disclosedtechniques, but do not necessarily require realization by differenthardware units. Rather, as described above, various units may becombined in a hardware unit or provided by a collection ofinteroperative hardware units, including one or more processors asdescribed above, in conjunction with suitable software and/or firmware.

Various embodiments have been described. These and other embodiments arewithin the scope of the following claims.

What is claimed is:
 1. A method implemented by one or more processors,the method comprising: receiving an indication of satisfaction, of acondition, of a routine that is assigned to a particular user; and inresponse to receiving the indication of satisfaction of the condition:executing the routine, executing the routine including causing a firstcomputing device associated with the particular user to execute a firstaction of the routine and causing a second computing device associatedwith the particular user to execute a second action of the routine;subsequent to executing the routine: determining that a new computingdevice, that was not previously associated with the particular user, isnow associated with the particular user; determining a new action thatis executable by the new computing device; and based on the newcomputing device being associated with the particular user, and the newaction being executable by the new computing device: customizing theroutine by adding the new action to the routine; and subsequent tocustomizing the routine: receiving an additional indication ofsatisfaction of the condition of the routine; and in response toreceiving the additional indication of satisfaction of the condition:executing the routine as customized, executing the routine as customizedincluding causing the first computing device to execute the firstaction, causing the second computing device to execute the secondaction, and causing the new computing device to execute the new action.2. The method of claim 1, further comprising: based on the new computingdevice being associated with the particular user, and the new actionbeing executable the new computing device: outputting an indication ofthe new action; and receiving, responsive to outputting the indicationof the new action, a command to add the new action to the routine;wherein customizing the routine is in response to receiving the commandto add the new action to the routine.
 3. The method of claim 1, whereinthe new computing device is an assistant enabled vehicle.
 4. The methodof claim 3, wherein the new action includes remotely starting theassistant enabled vehicle or adjusting a cabin temperature of the vassistant enabled ehicle.
 5. The method of claim 1, wherein theindication of the satisfaction of the condition is received in responseto a determination that a particular command was spoken and was directedto the automated assistant.
 6. The method of claim 5, wherein theindication of the satisfaction of the condition is received further inresponse to a determination, using a voice fingerprint, that theparticular user spoke the particular command.
 7. The method of claim 1,further comprising: determining an additional new action that isexecutable by the new computing device; and based on the new computingdevice being associated with the particular user, and the additional newaction being executable by the new computing device: customizing theroutine by adding the additional new action to the routine; whereinexecuting the routine as customized further includes causing the newcomputing device to execute the additional new action.
 8. A systemcomprising: one or more storage devices storing instructions; one ormore computers operable to execute the instructions to perform actionscomprising: receiving an indication of satisfaction, of a condition, ofa routine that is assigned to a particular user; and in response toreceiving the indication of satisfaction of the condition: executing theroutine, executing the routine including causing a first computingdevice associated with the particular user to execute a first action ofthe routine and causing a second computing device associated with theparticular user to execute a second action of the routine; subsequent toexecuting the routine: determining that a new computing device, that wasnot previously associated with the particular user, is now associatedwith the particular user; determining a new action that is executable bythe new computing device; and based on the new computing device beingassociated with the particular user, and the new action being executableby the new computing device: customizing the routine by adding the newaction to the routine; and subsequent to customizing the routine:receiving an additional indication of satisfaction of the condition ofthe routine; and in response to receiving the additional indication ofsatisfaction of the condition: executing the routine as customized,executing the routine as customized including causing the firstcomputing device to execute the first action, causing the secondcomputing device to execute the second action, and causing the newcomputing device to execute the new action.
 9. The system of claim 8,wherein the one or more computers are operable to execute theinstructions to perform further actions comprising: based on the newcomputing device being associated with the particular user, and the newaction being executable the new computing device: outputting anindication of the new action; and receiving, responsive to outputtingthe indication of the new action, a command to add the new action to theroutine; wherein customizing the routine is in response to receiving thecommand to add the new action to the routine.
 10. The system of claim 9,wherein the new computing device is a new assistant enabled vehicle. 11.The System of claim 10, wherein the new action includes remotelystarting the new assistant enabled vehicle or adjusting a cabintemperature of the new assistant enabled vehicle.
 12. The method ofclaim 10, wherein the indication of the satisfaction of the condition isreceived in response to a determination that a particular command wasspoken and was directed to the automated assistant.
 13. The system ofclaim 12, wherein the indication of the satisfaction of the condition isreceived further in response to a determination, using a voicefingerprint, that the particular user spoke the particular command. 14.The system of claim 8, wherein the one or more computers are operable toexecute the instructions to perform further actions comprising:determining an additional new action that is executable by the newcomputing device; and based on the new computing device being associatedwith the particular user, and the additional new action being executableby the new computing device: customizing the routine by adding theadditional new action to the routine; wherein executing the routine ascustomized further includes causing the new computing device to executethe additional new action.
 15. The system of claim 8, wherein the newcomputing device is a new assistant enabled vehicle.
 16. The System ofclaim 15, wherein the new action includes remotely starting the newassistant enabled vehicle or adjusting a cabin temperature of the newassistant enabled vehicle.
 17. The method of claim 8, wherein theindication of the satisfaction of the condition is received in responseto a determination that a particular command was spoken and was directedto the automated assistant.
 18. The system of claim 17, wherein theindication of the satisfaction of the condition is received further inresponse to a determination, using a voice fingerprint, that theparticular user spoke the particular command.